Relative quantification of differing proteins requires accurate estimation of the percentage of molecules retained during the MS workflow from sample preparation to detection. This percentage we call a molecule's efficiency. This work presents the aspect of the label-free absolute quantification project Quasar that aims to predict such efficiencies. In detail we use a support vector regression approach where quantifyable peptide properties are mapped to the efficiency. As training data we apply efficiency estimates obtained from spiked-in proteins.